In this paper, we describe the results of the participation of the Information Management Systems (IMS) group at CLEF eHealth 2020 Task 2, Consumer Health Search Task. In particular, we participated in both subtasks: Ad-hoc IR and Spoken queries retrieval. The goal of our work was to evaluate the reciprocal ranking fusion approach over 1) different query variants; 2) different retrieval functions; 3) w/out pseudo-relevance feedback. The results show that, on average, the best performances are obtained by a ranking fusion approach together with pseudo-relevance feedback.

A Study on Reciprocal Ranking Fusion in Consumer Health Search. MS UniPD at CLEF eHealth 2020 Task 2

Di Nunzio G. M.
;
Marchesin S.
;
Vezzani F.
2020

Abstract

In this paper, we describe the results of the participation of the Information Management Systems (IMS) group at CLEF eHealth 2020 Task 2, Consumer Health Search Task. In particular, we participated in both subtasks: Ad-hoc IR and Spoken queries retrieval. The goal of our work was to evaluate the reciprocal ranking fusion approach over 1) different query variants; 2) different retrieval functions; 3) w/out pseudo-relevance feedback. The results show that, on average, the best performances are obtained by a ranking fusion approach together with pseudo-relevance feedback.
2020
CEUR Workshop Proceedings
11th Conference and Labs of the Evaluation Forum, CLEF 2020
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3452910
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